1 citations · 1 across the 3 of their papers we have counts for
6 papers
A Marketplace for AI-Generated Adult Content and Deepfakes
Shalmoli Ghosh, Matthew R. DeVerna, Filippo Menczer
Generative AI systems increasingly enable the production of highly realistic synthetic media. Civitai, a popular community-driven platform for AI-generated content, operates a mone…
How the cascade inference problem distorts information diffusion
Matthew R. DeVerna, Francesco Pierri, Rachith Aiyappa +3
To analyze the flow of information online, experts often rely on platform-provided data from social media companies, which typically attribute all resharing actions to an original…
The Invisible Risks of AI-Generated Health Information
Matthew R. DeVerna, Harry Yaojun Yan, Kai-Cheng Yang +1
Generative artificial intelligence (AI) systems now summarize health-related search results, answer medical questions, and offer guidance people once sought from clinicians. These…
Large Language Models Require Curated Context for Reliable Political Fact-Checking -- Even with Reasoning and Web Search
Matthew R. DeVerna, Kai-Cheng Yang, Harry Yaojun Yan +1
Large language models (LLMs) have raised hopes for automated end-to-end fact-checking, but prior studies report mixed results. As mainstream chatbots increasingly ship with reasoni…
A longitudinal analysis of misinformation, polarization and toxicity on Bluesky after its public launch
Gianluca Nogara, Erfan Samieyan Sahneh, Matthew R. DeVerna +5
Bluesky is a decentralized, Twitter-like social media platform that has rapidly gained popularity. Following an invite-only phase, it officially opened to the public on February 6t…
Modeling the amplification of epidemic spread by individuals exposed to misinformation on social media
Matthew R. DeVerna, Francesco Pierri, Yong-Yeol Ahn +3
Understanding how misinformation affects the spread of disease is crucial for public health, especially given recent research indicating that misinformation can increase vaccine he…